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http://dbpedia.org/ontology/abstract Tissue image cytometry or tissue cytometryTissue image cytometry or tissue cytometry is a method of digital histopathology and combines classical digital pathology (glass slides scanning and virtual slide generation) and computational pathology (digital analysis) into one integrated approach with solutions for all kinds of diseases, tissue and cell types as well as molecular markers and corresponding staining methods to visualize these markers. Tissue cytometry uses virtual slides as they can be generated by multiple, commercially available slide scanners, as well as dedicated image analysis software – preferentially including machine and deep learning algorithms. Tissue cytometry enables cellular analysis within thick tissues, retaining morphological and contextual information, including spatial information on defined cellular subpopulations. In this process, a tissue sample, either formalin-fixed paraffin-embedded (FFPE) or frozen tissue section, also referred to as “cryocut”, is labelled with either immunohistochemistry(IHC) or immunofluorescent markers, scanned with high-throughput slide scanners and the data gathered from virtual slides is processed and analyzed using software that is able to identify individual cells in tissue context automatically and distinguish between nucleus and cytoplasm for each cell. Additional algorithms can identify cellular membranes, subcellular structures (like cytoskeletal fibers, vacuoles, nucleoli) and/or multicellular tissue structures (glands, glomeruli, epidermis, or tumor foci). Fluorescence Activated Cell Sorting (FACS) is a method of analysis that measures fluorescence signals on single cells, where the signal comes from antibody-mediated staining techniques and phenotypes detected by flow cytometry. The major limitation of flow cytometry is that it can only be applied – as the name suggest – to cells in solution. Although methods of “solubilizing” solid tissue exist, any such processing irrevocably destroys the tissue architecture and any spatial context. Hence, tissue cytometry complements the use of flow cytometry and fluorescence microscope in basic research, clinical practice, and clinical trials by providing FACS-like analyses on solid tissue sections (as well as adherent cell cultures) in situ. The advantage of tissue cytometry against flow cytometry is that tissue cytometry does not require the cells to be suspended in fluid, aiding in maintaining the integrity of the tissue structure, morphology, and contextual information, further assisting in precise and accurate contextual analysis that are not possible in flow cytometry.s that are not possible in flow cytometry.
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rdfs:comment Tissue image cytometry or tissue cytometryTissue image cytometry or tissue cytometry is a method of digital histopathology and combines classical digital pathology (glass slides scanning and virtual slide generation) and computational pathology (digital analysis) into one integrated approach with solutions for all kinds of diseases, tissue and cell types as well as molecular markers and corresponding staining methods to visualize these markers. Tissue cytometry uses virtual slides as they can be generated by multiple, commercially available slide scanners, as well as dedicated image analysis software – preferentially including machine and deep learning algorithms. Tissue cytometry enables cellular analysis within thick tissues, retaining morphological and contextual information, including spatial information on defined cellular suspatial information on defined cellular su
rdfs:label Tissue cytometry
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